| Autor: |
Yi-Xuan Lu, Jie-Sheng Wang, Sha-Sha Guo |
| Předmět: |
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| Zdroj: |
IAENG International Journal of Computer Science; Nov2019, Vol. 46 Issue 4, p1-9, 9p |
| Abstrakt: |
The path planning problem refers to find the shortest path to reach the predetermined target position in a certain complex environment. Particle swarm optimization (PSO) algorithm is derived from the imitation of the population cooperation of the flock and the predatory behavior of the competition. The sharing of information by the individuals in the swarm makes the movement of the whole swarm in the problem solution space from disorder process to order process. In this paper, the improved PSO algorithm based on improved inertia weights is adopted to solve the path planning problems. For the three constructed different maps, the improved PSO algorithm based on five different inertia weight adjustment strategies is used to solve the path planning problems. The simulation results are used to verify the effectiveness of the proposed algorithm and inertia weight adjustment strategies. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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